Description:
A data scientist working at the intersection of smart building technology, IoT, energy optimisation and predictive analytics. Working with rich telemetry from connected building assets, energy data and environmental inputs to deliver intelligent, scalable and automated insights. The work carried out will directly drive operational efficiencies, reduce energy consumption and improve system reliability for customers.
- Perform statistical analysis and deep data interrogation across diverse datasets.
- Develop, test and deploy advanced analytics frameworks that uncover actionable insights.
- Design and implement end to end data science workflows.
- Translate R&D concepts and exploratory analysis into production ready algorithms and reusable components.
- Build machine learning models and design experiments to optimise building performance and asset control strategies.
- Select, apply and evaluate appropriate data science techniques (e.g., regression, classification, clustering, anomaly detection) based on the use case requirements.
- Work closely with internal teams to translate business needs into data led solutions.
- Present complex technical insights in a clear, concise manner to both technical and non technical stakeholders.
- Collaborate with customer success and delivery teams to ensure that models, analytics and insights align with customer needs and expectations.
- Maintain strong internal relationships, contributing to a shared culture of curiosity, continuous improvement and innovation.
- Conduct exploratory research and develop prototypes or proof of concept solutions to test hypotheses or emerging techniques.
- Remain up to date with developments in Artificial Intelligence/Machine learning.
- Contribute to the development of internal best practices, processes and documentation, to increase team effectiveness and reusability of work.
- Evaluate and select the most appropriate data mining models for specific projects
- Communicate complex data insihgts clearly and effectively to both technical and non technical audiences.
- Stay informed and up to date about emerging technologies and methodologies.
- Maintain curiosity and inspiure others about the value of data science.
- Build and maintain relationships.
Requirements
- A passion for data interrogation with strong analytical thinking and drive to uncover actionable insight.
- Proficiency in Python or R, using libraries such as pandas, NumPy, scikit-learn, TensorFlow or equivalent.
- Skilled in SQL.
- Experience working as a data scientist, preferably on client facing software solutions, within optimisation or energy focussed applications.
- Strong foundation in statistical techniques and machine learning, including regression, classification, clustering, time series analysis and pattern recognition.
- Degree in a quantitative discipline such as Applied Mathematics, Statistics, Computer Science, Engineering or Physics.
Desirable
- MSc or PhD in a quantitative field.
- Experience deploying machine learning models in a cloud environment.
- Experience using version control tools such as Git and working with cloud based data platforms.
- Exposure to Agile methodologies and cross functional team collaboration.
- Experience in energy, IoT, smart buildings or related domains.
- Curious, self motivated, and able to work independently.
- Comfortable with ambiguity and proactive in identifying opportunities.
- A team player with strong communication skills and a desire to share knowledge.